Henry Han, Jeffrey Yi-Lin Forrest, Jiacun Wang, Shuining Yuan, Fei Han, Diane Li
Software Engineering Empirical Research Radar
Explainable machine learning for high frequency trading dynamics discovery
Paper detail page in SEER Radar.
Information Sciences 2024
AI / LLM for SE; Industrial Software Engineering
Event-Time & Latency-Sensitive Trading
Abstract / Summary
FIDR-SCAN creates an interpretable map of high-frequency transactions through feature interpolation, dimensional reduction, clustering and trading markers, with applications to equity and cryptocurrency data. It is relevant as an explainable-signal baseline, while not replacing strict event-time, cost and holdout controls.
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